Short guide to the Semantic Web

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Key ingredients of the Semantic Web explained in 30 minutes.:

1. WHAT IS THE GOAL?
2. WHAT ARE THE BUILDING BLOCKS?
3. HOW DO WE CREATE THE GRAPH? WHY LINKED DATA?
4. SHORT INTRODUCTION TO ONTOLOGIE�S

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Short guide to the Semantic Web

  1. 1. The Semantic Weba short guide  Maciej  Dabrowski  macdab@gmail.com  
  2. 2. THE SEMANTIC WEBWHAT ISTHE GOAL? WHAT ARETHE BUILDING BLOCKS? HOW DO WE CREATETHE GRAPH?WHY LINKED DATA? SHORT INTROTO ONTOLOGIES
  3. 3. What’s in a page ? And in a link ??  ?  ?  
  4. 4. VISION FOR THE WEBTIM BERNERS-LEE,THE 1ST WORLD WIDE WEBCONFERENCE, GENEVA, MAY 1994: DESCRIBE DOCUMENTS IN MACHINE READIBLE FORM CREATE MEANINGFUL LINKS (“RELATIONSHIPVALUES”) “ONLY WHEN WE HAVETHIS EXTRA LEVEL OF SEMANTICSWILL WE BE ABLETO USE COMPUTER POWERTO HELPUS EXPLOITTHE INFORMATIONTO A GREATER EXTENTTHAN OUR OWN READING.”
  5. 5. Aims of the Semantic WebBRIDGINGTHE GAP BETWEEN A WEB OFDOCUMENTSTO A WEB OF DATA,WITHTYPED OBJECTS ANDTYPED RELATIONSHIPS ADDING MACHINE-READABLE METADATATO EXISTING CONTENT, SOTHATINFORMATION CAN BE PARSED, QUERIED,REUSED
  6. 6. Aims of the Semantic WebDEFINING SHARED SEMANTICS FORTHISMETADATATO ALLOW INTEROPERABILITYBETWEEN APPLICATIONS AND FORADVANCED PURPOSES, SUCH AS REASONING ENABLING MACHINE-READABLE KNOWLEDGEAT WEB SCALE, MAKING INFORMATION MOREEASYTO FIND AND PROCESS
  7. 7. The Semantic Web, circa 2010MOST STANDARDISATION WORK IS DONE INTHE W3C: HTTP://WWW.W3.ORG/ INCUBATOR GROUPS,WORKING GROUP,INTEREST GROUPS: WGS FOR SPARQL, RDB2RDF, RIF, ETC. HCLS IG, SOCIAL WEB XG, ETC.
  8. 8. Name everything
  9. 9. Identifying resources with URIsURIS ARE USEDTO IDENTIFY EVERYTHING IN AUNIQUE AND NON-AMBIGUOUS WAY NOT ONLY PAGES (AS ONTHE CURRENT WEB),BUT ANY RESOURCE (PEOPLE, DOCUMENTS,BOOKS, INTERESTS, ETC.) A URI FOR A PERSON IS DIFFERENT FROM A URIFOR A DOCUMENT ABOUTTHE PERSON,BECAUSE A PERSON IS NOT A DOCUMENT! e.g. http://deri.ie/user/maciej-dabrowski e.g. http://deri.ie/content/modelling-preference-relaxation-e-commerce
  10. 10. Defining assertions with RDF•  URIS IDENTIFY RESOURCES: •  WE USE RDF (RESOURCE DESCRIPTIONFRAMEWORK)TO DEFINE ASSERTIONSABOUTTHESE RESOURCES •  RDF IS A DATA MODEL;A DIRECTED, LABELEDGRAPH USING URIS •  RDF IS BASED ONTRIPLES: – <SUBJECT> <PREDICATE> <OBJECT>.!
  11. 11. Simple triplesMaciejDabrowskiMDabrowski-lecture3authorSemantic_WebIntroduction to theSemantic Webtitlesubject
  12. 12. Use Urishttp://example.org/maciej-dabrowskihttp://example.org/MDabrowski-lecture3http://example.org/authorhttp://example.org/Semantic_WebIntroduction to theSemantic Webhttp://example.org/titlehttp://example.org/subject
  13. 13. Abbreviating urisPREFIX ex: http://example.org/# ex:maciej = <http://example.org/#maciej> ex:maciej-dabrowskiex:MDabrowski-lecture3ex:authorex:Semantic_WebIntroduction to theSemantic Webex:titleex:subject
  14. 14. Reuse existing vocabulariesPREFIX dct: http://purl.org/dc/terms/ http://deri.ie/user/maciej-dabrowskihttp://example.org/MDabrowski-lecture3dct:creatorhttp://dbpedia.org/resource/Semantic_WebIntroduction to theSemantic Webdct:titledct:subject
  15. 15. RDF by example!!@prefix dct: <http://purl.org/dc/terms/> . !<http://example.org/dm110-semweb>!!dct:title “Introduction to the Semantic Web” ; !!dct:author <http://www.deri.ie/users/maciej-dabrowski> ; !!!dct:subject <http://dbpedia.org/resource/Semantic_Web> .!
  16. 16. RDFAA WAY OF EMBEDDING RDF IN (X)HTMLDOCUMENTS: ONE PAGE FOR BOTH HUMANS ANDMACHINES DON’T NEEDTO REPEATYOURSELF INTRODUCING NEW XHTML ATTRIBUTES CURRENT WORK IS ONGOING ON RDFa 1.1: FOR PROFILES, ETC.
  17. 17. RDFa example
  18. 18. Triples are everywhere!10/06/2013  SUBJECT  PREDICATE  OBJECT  PREDICATE  OBJECT  OBJECT  …  
  19. 19. Defining semantics with ontologies•  RDF PROVIDES A WAYTO WRITE ASSERTIONSABOUT URIS •  WHAT ABOUTTHE SEMANTICS OFTHESEASSERTIONS, E.G.TO STATETHAT HTTP://XMLNS.COM/FOAF/0.1/KNOWS IDENTIFIES ANACQUAINTANCE RELATIONSHIP? •  ONTOLOGIES PROVIDE COMMONSEMANTICS FOR RESOURCES ONTHESEMANTIC WEB
  20. 20. Ontologies consist mainly of classes andproperties– :Person a rdfs:Class .!– :father a rdfs:Property .!– :father rdfs:domain :Person .!– :father rdfs:range :Person .!:Maciej:Mark:father:Persona:Persona
  21. 21. Notable ontologiesSOCIAL NETWORKS AND SOCIAL DATA: FOAF, SIOC TAXONOMIES AND CONTROLLEDVOCABULARIES: SKOS, MOAT
  22. 22. Linked Data

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